Automating Case Reporting of Chlamydia and Gonorrhea to Public Health Authorities in Illinois Clinics: Implementation and Evaluation of Findings.

BACKGROUND: Chlamydia and gonorrhea cases continue to rise in Illinois, increasing by 16.4% and 70.9% in 2019, respectively, compared with 2015. Providers are required to report both chlamydia and gonorrhea, as mandated by public health laws. Manual reporting remains a huge burden; 90%-93% of cases were reported to Illinois Department of Public Health (IDPH) via electronic laboratory reporting (ELR), and the remaining were reported through web-based data entry platforms, faxes, and phone calls. However, cases reported via ELRs only contain information available to a laboratory facility and do not contain additional data needed for public health. Such data are typically found in an electronic health record (EHR). Electronic case reports (eCRs) were developed and automated the generation of case reports from EHRs to be reported to public health agencies. OBJECTIVE: Prior studies consolidated trigger criteria for eCRs, and compared with manual reporting, found it to be more complete. The goal of this project is to pilot standards-based eCR for chlamydia and gonorrhea. We evaluated the throughput, completeness, and timeliness of eCR compared to ELR, as well as the implementation experience at a large health center-controlled network in Illinois. METHODS: For this study, we selected 8 clinics located on the north, west, and south sides of Chicago to implement the eCRs; these cases were reported to IDPH. The study period was 52 days. The centralized EHR used by these clinics leveraged 2 of the 3 case detection scenarios, which were previously defined as the trigger, to generate an eCR. These messages were successfully transmitted via Health Level 7 electronic initial case report standard. Upon receipt by IDPH, these eCRs were parsed and housed in a staging database. RESULTS: During the study period, 183 eCRs representing 135 unique patients were received by IDPH. eCR reported 95% (n=113 cases) of all the chlamydia cases and 97% (n=70 cases) of all the gonorrhea cases reported from the participating clinical sites. eCR found an additional 14 (19%) cases of gonorrhea that were not reported via ELR. However, ELR reported an additional 6 cases of chlamydia and 2 cases of gonorrhea, which were not reported via eCR. ELR reported 100% of chlamydia cases but only 81% of gonorrhea cases. While key elements such as patient and provider names were complete in both eCR and ELR, eCR was found to report additional clinical data, including history of present illness, reason for visit, symptoms, diagnosis, and medications. CONCLUSIONS: eCR successfully identified and created automated reports for chlamydia and gonorrhea cases in the implementing clinics in Illinois. eCR demonstrated a more complete case report and represents a promising future of reducing provider burden for reporting cases while achieving greater semantic interoperability between health care systems and public health.

Automating Case Reporting of Chlamydia and Gonorrhea to Public Health Authorities in Oregon Clinics.

BACKGROUND: Optimizing sexually transmitted disease (STD) reporting to state public health authorities is important to reduce incidence and manage outbreaks of STDs. Electronic laboratory reporting (ELR) is the standard through which local clinics report STDs to state public health authority. Electronic case reporting (eCR) is an alternative approach which automates transmission of case reports to public health jurisdictions using electronic health record (EHR) data. METHODS: Working with 3 community health centers in Oregon between February 3, 2020 and May 15, 2020, we piloted an automated eCR approach for gonorrhea (GC) and chlamydia (CT) from these clinics to the Oregon Health Authority. We compared the eCR approach to the existing ELR approach to determine completeness of case reporting for GC/CT. RESULTS: A total of 365 eCRs from 206 unique patients were generated. Among 154 instances where the case detection logic was satisfied for CT, 37% (54 instances) were based on the presence of a diagnosis and 63% (97 instances) were based on laboratory data. Among 232 instances where logic was satisfied for GC, 44% (102 instances) reflected a diagnosis and 56% (130 instances) reflected laboratory results. Data completeness was uniformly equal or higher for eCRs versus ELRs. CONCLUSIONS: The eCR approach was successful in identifying CT and GC cases and provided a more complete set of information to assist public health authorities when compared with ELRs. Electronic case reporting has the potential to automate and relieve staff burden on an important reporting requirement for clinical providers.